The following background information may present examples of specific aspects of the prior art (e.g., without limitation, approaches, facts, or common wisdom) that, while expected to be helpful to further educate the reader as to additional aspects of the prior art, is not to be construed as limiting the present invention, or any embodiments thereof, to anything stated or implied therein or inferred thereupon.
Intelligent control systems for artificial intelligent agents provide improved ability to control such agents. However, many currently known systems may exhibit a variety of issues, such as brittleness and poor generalization, to name two of many.
By way of educational background, another aspect of the prior art generally useful to be aware of is that one currently known solution shows a learning control apparatus including a grouping unit for grouping at least one variable into a variable group in accordance with an estimated causal relationship, a determining unit for determining a behavior variable corresponding to each variable group, and a layering unit for layering, in accordance with variable groups and behavior variables. Another known solution teaches of a population of agents seeded with cognitive map variants characterizing different cultures or different affiliation, modifications including modification to weights of the cognitive map and structure of the cognitive map of a global best in a neighborhood imitated according to a weighted random selection based on commonality of node characteristic in the neighborhood. Yet another known solution discloses of a method for multiple cue integration based on a plurality of objects comprising the following steps: deriving a relationship of a plurality of objects as distance graphs and distance matrices based on a plurality of object cues; and optimizing integration of distance graphs and distance matrices by minimizing a distance between ideal transition probability matrix and transition matrix derived from cue integration. However, these solutions may not effectively organize the multiple and related behaviors of artificial intelligent agent systems. A solution which allowed access to policies within a space and allowed for organization of that space according to properties of policies would be desirable.
In view of the foregoing, it is clear that these traditional techniques are not perfect and leave room for more optimal approaches.
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